Data Scientist, Risk

About the role

Flutterwave is seeking a highly analytical and technically driven Data Scientist to join its dynamic Risk team. In this role you will help transition risk capabilities from reactive analytics to proactive predictive modeling, designing, training, and deploying robust machine learning models to detect fraud and assess risk.

Key responsibilities

• Design, develop, and optimize machine‑learning models for fraud detection, transaction monitoring, and risk mitigation.
• Collect, clean, and analyze massive transactional datasets to engineer predictive features and uncover emerging fraud trends.
• Partner with Engineering and MLOps to deploy models into production, monitor performance, track data drift, and retrain as needed.
• Translate model outputs into actionable business rules, balancing fraud prevention with user experience.
• Validate data accuracy, integrity, and consistency across all risk and ML pipelines.
• Maintain comprehensive documentation of model architectures, training data, and algorithmic decisions for audits and regulatory compliance.

Required profile

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• 3–5 years of proven experience building and deploying production‑grade machine‑learning models.
• Fintech or payments industry experience is required.
• Direct experience with fraud detection, credit risk, or AML models is a plus.
• Strong programming skills in Python and SQL, with deep proficiency in ML libraries such as Scikit‑Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Experience with cloud data warehouses like Redshift, Snowflake, or BigQuery.
• Excellent problem‑solving abilities and clear communication of complex concepts to non‑technical stakeholders.

Required skills

• Python
• SQL
• Scikit‑Learn, XGBoost, LightGBM, TensorFlow, PyTorch
• Redshift, Snowflake, BigQuery